Dataviz Challenge #5: The Answers!

I’ve been in love with diverging stacked bar charts since I saw Joe Mako’s submission to Cole Nussbaumer’s dataviz challenge last December. Joe made this contest-winning chart. But in Tableau! The amazing but expensive software!

Could I ever create one in Excel?!

Yes! Luckily I’d learned about the Values in Reverse Order feature from Stephanie Evergreen. With Joe’s inspiration and Stephanie’s strategy, I started making these beauties for myself in Excel.

I wanted to share the chart secrets with all of you, so last month, I challenged readers to re-create a diverging stacked bar chart like this one:

It looks like I’m not the only one who loves diverging stacked bar charts. Congratulations to the 12 contestants! In order of submission, they are:

David Napoli

Anjie Raber

David Bonachea

Sheila Robinson

Amanda Drescher

Kristin Minichello

@luno1972

Hornyik Jozsef (in d3! with code!)

Stephanie Evergreen

Angelina Lopez

Kevin Gilds

Praveen Gowda

Most contestants seized the opportunity to use their own datasets and made adjustments as needed. For example, Sheila’s dataset fit a traditional stacked bar chart better than a diverging stacked bar chart, and Anjie needed to display cut-off scores.

So how do you make these diverging stacked bar charts, anyways?! There are at least two strategies: Either a) create two separate charts, a strategy demonstrated in previous posts like this one, or b) use floating bars, a strategy demonstrated in previous posts like this one. Stephanie Evergreen blogged about strategy B a few weeks ago and her explanation is pretty awesome, so I’m going to focus on strategy A today.Want to learn more? I’ll be sharing my top 5 must-have chart strategies at the American Evaluation Association’s annual conference on Thursday, October 17.

For discussion: Nearly all of the contestants requested friendly feedback on their graphs. In most cases, contestants were trying these charts for the first time and thinking about whether or not these charts could be adapted for their datasets. What do you think?